The identification and subsequent measurement of source and load impedances are useful tools for assessing and evaluating stability of electrical power systems. The impedance of an alternating current (AC) electrical system may be measured by injecting a perturbation signal in the direct and quadrature (dq) reference frame of the system, and measuring the voltage and current response to the perturbation.
Problems arise in conventional impedance measurement methods, including low signal-to-noise ratio (SNR) and the presence of background noise, which can prevent accurate measurement. One conventional method to improve SNR is to increase the magnitude and power of the injected perturbation so that the resulting system voltage and current responses are larger compared to the background noise. However, there is a practical limit to increasing the injected perturbation before it noticeably affects and alters the operating point of the system being measured. Because of this, injected perturbation signals are typically small, such as on the order of 5% of the power level that the system is operating at during the measurement. Other methods for improving SNR include decreasing the frequency span (which increases the spectral density) and averaging of data taken over a longer span of time. Both of these methods, however, increase the overall measurement time and decrease accuracy due to an increased chance for system frequency drift during the measurement. Frequency drift during impedance measurement strongly affects measurement accuracy in conventional impedance measurement systems.
For online impedance measurements in three-phase AC systems, a conventional frequency sweep Fast Fourier Transform (FFT) method can take a long time and may not be practical in systems where the operating point cannot be maintained for a long time.
Therefore, there is a need for a system and method capable of taking advantage of short measuring times to yield increased measurement accuracy.